[Hiring] Head of AI @Esko, a Veralto company

Role Description

Imagine yourself doing meaningful work that makes an everyday impact on the world around you, growing your expertise and expanding your skillset with every project, and thriving in a supportive team environment that inspires you to strive for excellence.

TraceGains is at a pivotal moment in our AI transformation journey. We need an experienced AI leader to build the foundational data, MLOps, algorithms, agents, and infrastructure that will accelerate our AI initiatives and scale our capabilities across the organization.

Reporting to the Senior Vice President, Engineering, the Head of AI will:

• Lead the strategy, architecture, design, build, and evolution of TraceGains’ next-generation Agentic AI data platform.
• Enable self-service for data science and engineering teams.
• Establish privacy-first governance and production-grade MLOps practices.
• Lay the foundation for scalable, reliable AI delivery across all TraceGains’ products.
• Build and lead a platform team of both data engineers and AI/ML engineers.
• Make sound, budget-conscious platform decisions balancing accuracy, latency, reliability, and total cost of ownership.
• Lead technically-grounded AI governance and policy discussions and translate them into practical engineering standards and enforceable controls.
• Establish robust data and evaluation foundations.

A typical day will look like:

• Architecting a scalable, multi-tenant agentic AI data platform using the Azure technology stack.
• Designing a hybrid data architecture supporting operational systems, agentic AI workloads, and a knowledge graph.
• Building infrastructure utilizing vector and graph databases for RAG applications and semantic search.
• Designing and implementing a comprehensive MLOps platform.
• Building automated pipelines using Azure technologies for continuous integration and deployment.
• Implementing real-time inference infrastructure with monitoring, alerting, and automated drift detection.
• Developing high-performance graph query services and APIs for real-time access to supply chain relationships.
• Deploying automated validation, conflict resolution, and data quality monitoring.
• Implementing Infrastructure as Code (IaC) and building CI/CD pipelines for data products and ML models.
• Setting and enforcing platform standards for cost control, model/runtime selection, and performance targets.
• Leading AI governance with Security/Legal/Privacy.
• Building scalable data + evaluation systems.
• Creating self-service capabilities with comprehensive monitoring and observability.
• Driving engineering delivery improvements through AI-based code analysis.
• Staying on top of new research including cutting-edge AI technology.
• Democratizing AI through TraceGains teams for adoption and deployment across the platform.

Qualifications

• Master's degree in Computer Science, Data Engineering, or related field (or equivalent experience); Ph.D. is a plus.
• 10+ years building enterprise data and AI platforms in production environments.
• 2-3 years driving LLM adoption for Generative AI use cases.
• 1+ year(s) of building agentic systems including deployment of MCP servers to enable agentic AI.
• Proven ability to lead cost-aware AI delivery, technically grounded governance decisions, and large-scale evaluation/data practices.
• Proven track record designing and implementing MLOps platforms.
• Experience with Pipelines, model monitoring, and drift detection.
• Experience with graph databases and vector databases to support RAG.
• Ability to drive CI/CD for ML, security, safety, monitoring, and observability.
• Proven ability to establish shared platform capabilities that serve multiple product teams.
• Strong communication skills with ability to present to executive leadership.
• Track record of cross-functional collaboration with AI product teams, ML, and business stakeholders.
• Experience establishing technical standards and governance frameworks across distributed teams.
• Ability to be a team player, willing to grow and change and drive change into the organization in a positive and constructive manner.
• Experience mentoring technical teams (data engineers, AI/ML engineers, and platform engineers).
• Occasional travel required for department meetings, all company events, in-person seminars/networking events, etc.
• Successful completion of a drug and background screening process.

Requirements

• Experience building AI teams from 0 to 1.
• Experience developing and fine-tuning foundational models.
• Experience with infrastructure automation (IaC) via Terraform or similar technology.
• Proficient with Docker and Kubernetes.
• Experience with supply chain, food safety, or regulatory compliance domains.
• Multi-cloud architecture experience with Azure as primary and AWS/GCP familiarity.
• Knowledge of LLMs, RAG architectures, and advanced NLP applications.
• Open source contributions to ML or data platform tools.
• Experience with knowledge graphs and ontology management.
• Background in privacy-preserving ML techniques and federated learning.

Benefits

• Comprehensive package of benefits including paid time off.
• Medical/dental/vision insurance.
• 401(k) to eligible employees.